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Articles de revues sur le sujet « Recognition problem »

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Auteur : Grafiati
Publié le 25 mai 2024

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1

Džamonja, Mirna. « Measure recognition problem ». Philosophical Transactions of the Royal Society A : Mathematical, Physical and Engineering Sciences 364, no 1849 (19 octobre 2006) : 3171–82. http://dx.doi.org/10.1098/rsta.2006.1896.

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This is a paper in mathematics, specifically in set theory. On the example of the measure recognition problem (MRP), the paper highlights the phenomenon of the utility of a multidisciplinary mathematical approach to a single mathematical problem, in particular, the value of a set-theoretic analysis. MRP asks if for a given Boolean algebra, , and a property, Φ , of measures, one can recognize by purely combinatorial means if supports a strictly positive measure with property Φ . The most famous instance of this problem is MRP (countable additivity), and in the first part of the paper, we survey the known results on this and some other problems. We show how these results naturally lead to asking about two other specific instances of the problem MRP, namely MRP (non-atomic) and MRP (separable). Then, we show how our recent work gives an easy solution to the former of these problems and some partial information about the latter. The long-term goal of this line of research is to obtain a structure theory of Boolean algebras that support a finitely additive strictly positive measure, along the lines of Maharam theorem, which gives such a structure theorem for measure algebras.
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Sinnerbrink, Robert. « Recognitive Freedom : Hegel and the Problem of Recognition ». Critical Horizons 5, no 1 (19 février 2004) : 271–95. http://dx.doi.org/10.1163/1568516042653503.

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Kanyusik, Will. « The Problem of Recognition ». Journal of Literary & ; Cultural Disability Studies 6, no 2 (janvier 2012) : 159–74. http://dx.doi.org/10.3828/jlcds.2012.14.

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Daverman, Robert J., et Thomas L. Thickstun. « The 3-manifold recognition problem ». Transactions of the American Mathematical Society 358, no 12 (1 décembre 2006) : 5257–71. http://dx.doi.org/10.1090/s0002-9947-05-03786-4.

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Rukhin, Andrew L. « The Recognition Problem of Biometrics ». CHANCE 17, no 1 (janvier 2004) : 30–34. http://dx.doi.org/10.1080/09332480.2004.10554884.

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Kardava, Irakli, Jemal Antidze et Nana Gulua. « Solving the Problem of the Accents for Speech Recognition Systems ». International Journal of Signal Processing Systems 4, no 3 (juin 2016) : 235–38. http://dx.doi.org/10.18178/ijsps.4.3.235-238.

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Shastri, Lokendra, et Thomas Fontaine. « Character Recognition Digit Recognition Pattern Recognition Spatiotemporal Neural Networks Modular Networks Segmentation Problem ». Connection Science 7, no 3-4 (septembre 1995) : 211–46. http://dx.doi.org/10.1080/09540099509696192.

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Чалий, Ю. І. « Qualified Legislator’s Silence : Problem of Recognition ». Bulletin of Kharkiv National University of Internal Affairs 86, no 3 (24 septembre 2019) : 22–31. http://dx.doi.org/10.32631/v.2019.3.02.

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The problem of developing the ways of recognition of the qualified silence of the legislator has been studied. It has been stated that the “qualified silence of the legislator” is underdeveloped category of law, especially regarding the ways of recognizing such specific legislative silence within the norms of law. This problem has become more urgent due to the revival of case law in Ukraine on the application of the analogy of law and the analogy of legislation. While applying these techniques, overcoming the gaps of civil law, the courts often identify the relevant gaps of the legislation with the qualified silence of the legislator, which is a major shortcoming. Solution of this problem will allow the courts to better identify the qualified silence of the legislator in the law norms. One of the methodological approaches in solving the problem of recognition of the legislator’s qualified silence and the gaps of the legislation is the extension of the relevant research tools. In contrast to the legal position existing in the legal doctrine, the author of the article has critically assessed the ability of systematic interpretation of the law norms to be a self-sufficient method of revealing the legislator’s qualified silence. In order to recognize the true qualified silence of the legislator, the author has offered to concentrate on explaining the legal policy that may be manifested in one or other cases of the legislator’s silent expression of will. At the same time, systematic, historical or doctrinal interpretation of legislation is of relative importance to the need for clarifying legal policy. From the point of view of determining the degree of scientific novelty, the suggested approach has the nature of further development of doctrinal provisions. The author has noted on the necessity of further elaboration of the studied problems, in particular, in determining the location of each of the ways of recognizing the qualified silence of the legislator within the system of methods of interpretation of legal norms.
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Repovš, Dušan. « The recognition problem for topological manifolds ». Banach Center Publications 18, no 1 (1986) : 77–108. http://dx.doi.org/10.4064/-18-1-77-108.

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Melbourne, I. « The recognition problem for equivariant singularities ». Nonlinearity 1, no 1 (1 février 1988) : 215–40. http://dx.doi.org/10.1088/0951-7715/1/1/009.

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Prisner, Erich. « The recognition problem for line bigraphs ». Discrete Mathematics 268, no 1-3 (juillet 2003) : 243–56. http://dx.doi.org/10.1016/s0012-365x(02)00691-x.

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Hutchinson, Gordon. « International workshop tackles promoter recognition problem ». Trends in Genetics 12, no 4 (avril 1996) : 159. http://dx.doi.org/10.1016/0168-9525(96)30021-8.

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Bagram Sibgatullovich, Kochkarev. « Problem of Recognition of Hamiltonian Graph ». International Journal of Wireless Communications and Mobile Computing 4, no 2 (2016) : 52. http://dx.doi.org/10.11648/j.wcmc.20160402.17.

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14

Zou, W. W. W., et P. C. Yuen. « Very Low Resolution Face Recognition Problem ». IEEE Transactions on Image Processing 21, no 1 (janvier 2012) : 327–40. http://dx.doi.org/10.1109/tip.2011.2162423.

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15

Krylou, Y. V., et A. J. Perez Tchernov. « On the problem of domino recognition ». Electronic Notes in Discrete Mathematics 24 (juillet 2006) : 251–58. http://dx.doi.org/10.1016/j.endm.2006.06.029.

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Raevskii, O. A. « The problem of recognition in chemistry ». Theoretical and Experimental Chemistry 22, no 4 (1987) : 431–43. http://dx.doi.org/10.1007/bf00523821.

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17

Xiong, Yijie. « Face recognition based on machine learning ». Applied and Computational Engineering 6, no 1 (14 juin 2023) : 1100–1105. http://dx.doi.org/10.54254/2755-2721/6/20230407.

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Due to its widespread use, face recognition has emerged in the past 20 years as one of the most pervasive biometric identification technology disciplines. This paper briefly summarizes the history of face recognitions development, identifies the technologys present use cases, introduces the main methods of face recognition in detail from the perspective of machine learning and prospects for the future development of this technology. The result shows that this technology still faces many challenges, such as the problem of recognizing different expressions on the same face, the problem of recognizing twins and similar faces, the problem of using the color information of color face images efficiently and so on.
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Borisova, Irina A., et Nikolay G. Zagoruiko. « Problem SDX as the Extreme Case of Combined Type Recognition Problems ». Journal of Automation and Information Sciences 40, no 4 (2008) : 18–27. http://dx.doi.org/10.1615/jautomatinfscien.v40.i4.20.

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Yadav, Abhishek, et Sachin Mahajan. « Review on Face Detection and Recognition Technology Based on Neural Network ». Journal of Advance Research in Computer Science & ; Engineering (ISSN : 2456-3552) 4, no 2 (28 février 2017) : 01–07. http://dx.doi.org/10.53555/nncse.v4i2.400.

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In this paper, feature extraction and facial recognition are studied in order to resolve problems like highdimension problem, small size samples and no-linear separable problem that exist in facial recognition technology. In the part of feature extraction we use a HGPP algorithm, to extract the input features in building a face recognition system. The neural network, which represents brilliant performance on small training sets, non-linear separable and high-dimension pattern recognition problems in the recognition stage, is used for pattern classification. The proposed approach is validated with the ORL database. Experimental results demonstrate the effectiveness of this method in the performance of face recognition.
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20

CHENG, REI-HENG, CHI-WEI LEE et ZEN CHEN. « RECOGNITION OF RADICALS IN HANDWRITTEN CHINESE CHARACTERS BY MEANS OF PROBLEM REDUCTION AND KNOWLEDGE GUIDANCE ». International Journal of Pattern Recognition and Artificial Intelligence 10, no 06 (septembre 1996) : 657–77. http://dx.doi.org/10.1142/s0218001496000396.

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Recognizing handwritten Chinese characters is a complex problem. We break the problem down into a series of sub-problems and concentrate on the radical recognition problem. The sub-problems are linked in a hierarchy of three layers: radical, radical sub-unit, and salient stroke. This problem reduction technique enables us to solve complex recognition problems effectively. We describe how to analyze and choose radical sub-units and salient strokes in order to recognize a set of radicals. We also construct two knowledge bases in the form of decision trees to guide the hypothesis and test procedures used to solve the recognition sub-problems. The problem reduction is done in a top-down fashion, while the problem solving process proceeds in a bottom-up fashion. The advantages of our method are described. The representation and organization of the two knowledge bases are explicitly described. The method is tested on two sets of handprinted characters using an IBM PC (486-33). The recognition rate is over 95.7% and the computer time needed to recognize a radical averages about 0.07 s. The experimental results indicate that our method effectively copes with a wide range of ordinary variations encountered in handwritten Chinese characters.
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21

Camino García, I., et U. Zölzer. « Naval ship recognition ». Advances in Radio Science 10 (18 septembre 2012) : 141–44. http://dx.doi.org/10.5194/ars-10-141-2012.

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Abstract. Object recognition is a very interesting task with multiple applications and for that reason it has been dealt with very intensively in the last years. In particular, the application to naval ship pictures may facilitate the work of the coastguards or the navy. However, this type of images entails some difficulties due to their specific environment. Water reflects the light and as a consequence, some areas may presumably show different brightness and color. Waves from wind or moving ships pose a problem due to the additional edges that they produce. The camouflage of ships in the military context is also an issue to take into account. Therefore, it is difficult to propose a simple method that is valid for every image. A discussion about which techniques may solve these problems is presented and finally a combined solution based on contour recognition is suggested. Test images are preprocessed by histogram stretching. Then, the Canny method is applied to the image and to the reference contour in order to obtain not only their edges, but also their respective orientations. The problem of recognizing the reference contour within the detected edges is addressed by making use of the Generalized Hough Transform (GHT).
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22

Rozhnova, O. V., et T. V. Girka. « The problem of recognition the intangible assets ». Izvestiya MGTU MAMI 7, no 1-5 (10 septembre 2013) : 77–80. http://dx.doi.org/10.17816/2074-0530-67791.

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The article discusses topical issues of recognition the intangible assets, criticizes some rules of their recognition, which are set in international financial reporting standards. There are made proposals to improve the procedure of recognition the intangible assets according to the first decade of XXI century economic situation.
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23

Cui, Zongyong, Zongjie Cao, Jianyu Yang et Hongliang Ren. « Hierarchical Recognition System for Target Recognition from Sparse Representations ». Mathematical Problems in Engineering 2015 (2015) : 1–6. http://dx.doi.org/10.1155/2015/527095.

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A hierarchical recognition system (HRS) based on constrained Deep Belief Network (DBN) is proposed for SAR Automatic Target Recognition (SAR ATR). As a classical Deep Learning method, DBN has shown great performance on data reconstruction, big data mining, and classification. However, few works have been carried out to solve small data problems (like SAR ATR) by Deep Learning method. In HRS, the deep structure and pattern classifier are combined to solve small data classification problems. After building the DBN with multiple Restricted Boltzmann Machines (RBMs), hierarchical features can be obtained, and then they are fed to classifier directly. To obtain more natural sparse feature representation, the Constrained RBM (CRBM) is proposed with solving a generalized optimization problem. Three RBM variants,L1-RNM,L2-RBM, andL1/2-RBM, are presented and introduced to HRS in this paper. The experiments on MSTAR public dataset show that the performance of the proposed HRS with CRBM outperforms current pattern recognition methods in SAR ATR, like PCA + SVM, LDA + SVM, and NMF + SVM.
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Hsu, Wei Chih, et Tsan Ying Yu. « A Novel Creative Thinking Model to Pattern Recognition Problem Solving ». Applied Mechanics and Materials 145 (décembre 2011) : 598–602. http://dx.doi.org/10.4028/www.scientific.net/amm.145.598.

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Inspired by the studies of modern cognitive psychology and real-world pattern recognition systems, a new developed model for pattern recognition is proposed to provide an alternative solution for some complicated pattern recognition problems. This study exploits a creative problem solving (CPS) skill to derive a pattern recognition solution and presents the basic principles, criteria, and techniques for CPS. Next, CPS is devoted to develop pattern recognition application and demonstrate a case study. In addition, this paper discusses the case study on the application of CPS thinking model. Experiment results show that CPS thinking model can improve this application performance of pattern recognition.
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Chen, Yu Han, et Ming Cheng. « Using Petri Net to Plan Recognition ». Applied Mechanics and Materials 411-414 (septembre 2013) : 2119–24. http://dx.doi.org/10.4028/www.scientific.net/amm.411-414.2119.

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Plan recognition is an important problem to address in order to enhance the capabilities of battlefield surveillance systems. It is concerned with finding a priori defined plan that possibly are instantiated in the present flow of battle events. Plan recognition requires that many sub problems are solved. For instance, we need to establish which situations are interesting, how to represent these situations, and inferable events and states that can be used for representing them. In this paper we discuss current research efforts and goals concerning template-based plan recognition. We provide a categorization of approaches for plan recognition together with a formalization of the template-based plan recognition problem. We discuss this formalization in the light of an air-ground striking scenario. Finally, we conclude that plan recognition is an important problem to look into for enhancing the overall situation awareness of decision makers.
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Simpson, Cathy A., et Jalie A. Tucker. « Temporal sequencing of alcohol-related problems, problem recognition, and help-seeking episodes ». Addictive Behaviors 27, no 5 (septembre 2002) : 659–74. http://dx.doi.org/10.1016/s0306-4603(01)00200-3.

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Teng, Xiu Hua. « The Application of Image Processing Technology in the Intelligent Transportation System ». Applied Mechanics and Materials 543-547 (mars 2014) : 2678–80. http://dx.doi.org/10.4028/www.scientific.net/amm.543-547.2678.

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Image processing-based vehicle recognition is one of the important research fields in ITS. The existing methods are all based on license plate recognition and car shape recognition. Their common problem is algorithm stability. And the license plates are easy to be changed. All information about vehicles should be used to recognize them reliably. A problem to be solved is to find a method to recognize vehicles besides license plate recognition and vehicle model recognition. Vehicle license plate location and character segmentation are critical steps in the license plate recognition system, and yet there are difficult problems to be solved. Kernel density estimation and Mean Shift theory
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Chavkina, S. « Public Opinion Recognition Problem in Public Management ». Advanced Science Journal 2014, no 4 (31 mars 2014) : 95–98. http://dx.doi.org/10.15550/asj.2014.04.095.

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Beisegel, Jesse, Carolin Denkert, Ekkehard Köhler, Matjaž Krnc, Nevena Pivač, Robert Scheffler et Martin Strehler. « The Recognition Problem of Graph Search Trees ». SIAM Journal on Discrete Mathematics 35, no 2 (janvier 2021) : 1418–46. http://dx.doi.org/10.1137/20m1313301.

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Cowan, David A. « Developing a Process Model of Problem Recognition ». Academy of Management Review 11, no 4 (octobre 1986) : 763. http://dx.doi.org/10.2307/258395.

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Satarov, Georgy. « INSTITUTES OF CHAOS : THE PROBLEM OF RECOGNITION ». Journal of Political Theory, Political Philosophy and Sociology of Politics Politeia 50, no 3 (2008) : 45–66. http://dx.doi.org/10.30570/2078-5089-2008-50-3-45-66.

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Gorman, John W., et Frank P. Kuhl. « Partial shape recognition as an optimization problem ». Remote Sensing Reviews 6, no 1 (janvier 1992) : 207–27. http://dx.doi.org/10.1080/02757259209532153.

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Cowan, David A. « Developing a Process Model of Problem Recognition ». Academy of Management Review 11, no 4 (octobre 1986) : 763–76. http://dx.doi.org/10.5465/amr.1986.4283930.

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Workman, Jane E., et Cathryn M. Studak. « Fashion consumers and fashion problem recognition style ». International Journal of Consumer Studies 30, no 1 (janvier 2006) : 75–84. http://dx.doi.org/10.1111/j.1470-6431.2005.00451.x.

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Sharma, Akshaya Kumar, et Amit Shrivastava. « Problem Definition on Face Recognition : A Review ». Asian Journal of Advanced Basic Sciences 7, no 1 (28 février 2019) : 13–17. http://dx.doi.org/10.33980/ajabs.2019.v07i01.002.

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Rezaei Fard, E., et K. Aghayar. « Quantum Adiabatic Evolution for Pattern Recognition Problem ». Chinese Physics Letters 34, no 12 (décembre 2017) : 120302. http://dx.doi.org/10.1088/0256-307x/34/12/120302.

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Trouvé, Alain, Mauro Piccioni et Sergio Scarlatti. « A Variational Problem Arising from Speech Recognition ». SIAM Journal on Applied Mathematics 58, no 3 (juin 1998) : 753–71. http://dx.doi.org/10.1137/s0036139995292537.

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SCARBOROUGH, ELIZABETH. « Recognition for Women : The Problem of Linkage ». Annals of the New York Academy of Sciences 727, no 1 Aspects of th (octobre 1994) : 101–12. http://dx.doi.org/10.1111/j.1749-6632.1994.tb27503.x.

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McCrory, S., DF Smith et AJ Larner. « Facing up to a problem with recognition ». British Journal of Hospital Medicine 80, no 5 (2 mai 2019) : 288–89. http://dx.doi.org/10.12968/hmed.2019.80.5.288.

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Barczentewicz, Mikołaj. « The Illuminati Problem and Rules of Recognition ». Oxford Journal of Legal Studies 38, no 3 (2018) : 500–527. http://dx.doi.org/10.1093/ojls/gqy014.

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Chandrasekaran, R. « Recognition of Gilmore-Gomory traveling salesman problem ». Discrete Applied Mathematics 14, no 3 (juillet 1986) : 231–38. http://dx.doi.org/10.1016/0166-218x(86)90027-2.

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KLEIN, G. « Aluminum : new recognition of an old problem ». Current Opinion in Pharmacology 5, no 6 (décembre 2005) : 637–40. http://dx.doi.org/10.1016/j.coph.2005.07.005.

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Ferm�ller, Cornelia. « Passive navigation as a pattern recognition problem ». International Journal of Computer Vision 14, no 2 (mars 1995) : 147–58. http://dx.doi.org/10.1007/bf01418980.

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Dvoenko, S. D., A. V. Kopylov et V. V. Mottl. « The Problem of Pattern Recognition in Arrays of Interconnected Objects. Statement of the Recognition Problem and Basic Assumptions ». Automation and Remote Control 65, no 1 (janvier 2004) : 127–41. http://dx.doi.org/10.1023/b:aurc.0000011696.31008.5a.

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Lipeika, Antanas, et Joana Lipeikienė. « Time alignment in speech and speaker recognition ». Lietuvos matematikos rinkinys 41 (17 décembre 2001) : 584–90. http://dx.doi.org/10.15388/lmr.2001.34736.

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Hurst, Keith, Anne Dean MPhil et Stuart Trickey. « The recognition and non-recognition of problem-solving stages in nursing practice ». Journal of Advanced Nursing 16, no 12 (décembre 1991) : 1444–55. http://dx.doi.org/10.1111/j.1365-2648.1991.tb01592.x.

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Dvoenko, S. D., A. V. Kopylov et V. V. Mottl. « A Problem of Pattern Recognition in Arrays of Interrelated Objects. Recognition Algorithm ». Automation and Remote Control 66, no 12 (décembre 2005) : 2019–32. http://dx.doi.org/10.1007/s10513-005-0232-9.

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Жданова, O. Zhdanova, Макарова et I. Makarova. « OBJECT RECOGNITION SYSTEM ON THE ROAD ». Alternative energy sources in the transport-technological complex : problems and prospects of rational use of 3, no 1 (16 mars 2016) : 224–27. http://dx.doi.org/10.12737/17900.

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This article outlines the existing safety problems on the road, describes the existing recognition systems of well-known automobile manufacturers, and considers advantages and disadvantages of existing solutions. The general scheme of solving the problem of objects detection and recognition was showed.
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Wang, Shou Feng, et Lin Zhang. « Approach to Intent Recognize Based on Petri Nets ». Applied Mechanics and Materials 644-650 (septembre 2014) : 1126–31. http://dx.doi.org/10.4028/www.scientific.net/amm.644-650.1126.

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Intent recognition is an important problem to address in order to enhance the capabilities of battlefield surveillance systems. It is concerned with finding a priori defined template that possibly are instantiated in the present flow of battle events. Intent recognition requires that many sub problems are solved. For instance, we need to establish which actions are interesting, how to represent these actions, and inferable events and states that can be used for representing them. In this paper we discuss current research efforts and goals concerning template-based intent recognition. We provide a categorization of approaches for intent recognition together with a formalization of the template-based intent recognition problem. We discuss this formalization in the light of an air-ground striking scenario. Finally, we conclude that intent recognition is an important problem to look into for enhancing the overall situation awareness of decision makers.
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Dranseika, Vilius. « VEIKSMŲ ATPAŽINIMAS KAIP VIRTUS DORMITIVA ». Problemos 77 (1 janvier 2010) : 122–28. http://dx.doi.org/10.15388/problemos.2010.0.1896.

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Straipsnyje siūlomos konceptualios priemonės, leidžiančios formuluoti tvirtinimą, kad tose socialinių mokslų filosofijos teorijose, kuriose veiksmų atpažinimas yra laikomas metodologiniu socialinio aiškinimo pagrindu, jis yra traktuojamas kaip „virtus dormitiva“. Tuomet veiksmų atpažinimas gali būti suprantamas kaip tiesioginė veiksmų tipų įžvalga elgsenoje arba neapibrėžta, holistinė veiksmų interpretavimo procedūra. Abiem atvejais susiduriama su neskaidrios ir toliau neaiškinamos pažįstančiojo episteminės galios postulavimu. „Virtus dormitiva“ problema tampa ypač aštri, jei pripažįstame veiksmo atpažinimo problemos metodologinį pirmumą prieš veiksmo aiškinimo problemą1.Pagrindiniai žodžiai: veiksmų atpažinimas, veiksmų aiškinimas, veiksmų tipai ir atvejai, socialinių mokslų filosofija.Action Recognition as Virtus DormitivaVilius Dranseika SummaryIn this paper, I propose the conceptual means that allow for the formulation of the claim that in the theories of philosophy of social science that take action recognition as the methodological basis of social explanation, action recognition is treated as a virtus dormitiva. Here action recognition may be understood either as a direct perception of action-types in behaviour or as an indeterminate holistic procedure of action interpretation. In both cases we encounter positing of nontransparent and further unexplainable epistemic power. The problem of virtus dormitiva becomes especially pressing if we recognize the methodological primacy of the problem of action recognition over the problem of action explanation.Keywords: action recognition, explanation of actions, action types and act tokens, philosophy of social sciences.
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